Aaliya Taiyab, Md Nayab Sulaimani, Aanchal Rathi, Fazlurrahman Khan, Afzal Hussain, Mohamed F. Alajmi, Md. Imtaiyaz Hassan
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引用次数: 0
Abstract
Cancer cells exhibit elevated levels of reactive oxygen species, resulting in oxidative stress and DNA damage. To counteract this, many cancers upregulate the expression of MTH1 (MutT Homolog-1), a crucial enzyme that detoxifies oxidised nucleotide pools. Consequently, inhibiting MTH1 is a potential therapeutic strategy for managing DNA damage and cancer cell death. Here, we conducted a comprehensive computational screening of 3800 FDA-approved drugs to identify potential MTH1 inhibitors. Among these, Lumacaftor and Nilotinib were selected based on their strong binding affinity and pharmacokinetic profiles. Molecular dynamics simulations over 500 ns further validated the stable binding of these drugs to MTH1, suggesting their potential as effective inhibitors. Nilotinib, a well-known tyrosine kinase inhibitor (TKI), displayed strong binding affinity (Ka = 2.5 × 104) and potent MTH1 inhibitory activity (IC50: 37.2 μM). Notably, this study is the first to establish the interaction between Nilotinib and MTH1, highlighting the dual potential of Nilotinib as an MTH1 inhibitor. The findings suggest that Nilotinib could be repurposed to enhance cancer therapy, particularly in combating drug resistance through the novel mechanism of MTH1 inhibition. This approach provides new avenues for tackling chemoresistance and improving therapeutic outcomes in cancer patients.
期刊介绍:
Journal of Molecular Recognition (JMR) publishes original research papers and reviews describing substantial advances in our understanding of molecular recognition phenomena in life sciences, covering all aspects from biochemistry, molecular biology, medicine, and biophysics. The research may employ experimental, theoretical and/or computational approaches.
The focus of the journal is on recognition phenomena involving biomolecules and their biological / biochemical partners rather than on the recognition of metal ions or inorganic compounds. Molecular recognition involves non-covalent specific interactions between two or more biological molecules, molecular aggregates, cellular modules or organelles, as exemplified by receptor-ligand, antigen-antibody, nucleic acid-protein, sugar-lectin, to mention just a few of the possible interactions. The journal invites manuscripts that aim to achieve a complete description of molecular recognition mechanisms between well-characterized biomolecules in terms of structure, dynamics and biological activity. Such studies may help the future development of new drugs and vaccines, although the experimental testing of new drugs and vaccines falls outside the scope of the journal. Manuscripts that describe the application of standard approaches and techniques to design or model new molecular entities or to describe interactions between biomolecules, but do not provide new insights into molecular recognition processes will not be considered. Similarly, manuscripts involving biomolecules uncharacterized at the sequence level (e.g. calf thymus DNA) will not be considered.